Jakob Ambsdorf
@jakamb.bsky.social
Reposted by Jakob Ambsdorf
Deadline extended!
Interested in foundation models for brain MRI? You still have time to participate in the FOMO25 Challenge! Deadline has been extended until August 31, 2025.
To get started, check out:
🌍 website: fomo25.github.io
💻 code: lnkd.in/d8W8k9aV
🤗 checkpoints: lnkd.in/dZESityQ
Interested in foundation models for brain MRI? You still have time to participate in the FOMO25 Challenge! Deadline has been extended until August 31, 2025.
To get started, check out:
🌍 website: fomo25.github.io
💻 code: lnkd.in/d8W8k9aV
🤗 checkpoints: lnkd.in/dZESityQ
FOMO 2025 - Foundation Model Challenge for Brain MRI
fomo25.github.io
August 19, 2025 at 6:30 PM
Deadline extended!
Interested in foundation models for brain MRI? You still have time to participate in the FOMO25 Challenge! Deadline has been extended until August 31, 2025.
To get started, check out:
🌍 website: fomo25.github.io
💻 code: lnkd.in/d8W8k9aV
🤗 checkpoints: lnkd.in/dZESityQ
Interested in foundation models for brain MRI? You still have time to participate in the FOMO25 Challenge! Deadline has been extended until August 31, 2025.
To get started, check out:
🌍 website: fomo25.github.io
💻 code: lnkd.in/d8W8k9aV
🤗 checkpoints: lnkd.in/dZESityQ
Reposted by Jakob Ambsdorf
Training a custom foundation model for your niche imaging domain? In our #MICCAI2025 paper, we demonstrate on fetal ultrasound: A smaller model on less data wins when trained in-domain, while generalist models fail to show benefits of scaling.
arxiv.org/abs/2506.19552
arxiv.org/abs/2506.19552
General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound
With access to large-scale, unlabeled medical datasets, researchers are confronted with two questions: Should they attempt to pretrain a custom foundation model on this medical data, or use transfer-l...
arxiv.org
July 17, 2025 at 3:48 PM
Training a custom foundation model for your niche imaging domain? In our #MICCAI2025 paper, we demonstrate on fetal ultrasound: A smaller model on less data wins when trained in-domain, while generalist models fail to show benefits of scaling.
arxiv.org/abs/2506.19552
arxiv.org/abs/2506.19552
Reposted by Jakob Ambsdorf
FOMO25 accepted at #MICCAI2025! 🚀
Excited to announce the first challenge at MICCAI focusing on the development of self-supervised pretraining of foundation models for brain MRI! 🧠
With access to a large-scale dataset, codebase, cash prices and multiple tracks.
Read more ⬇️
Excited to announce the first challenge at MICCAI focusing on the development of self-supervised pretraining of foundation models for brain MRI! 🧠
With access to a large-scale dataset, codebase, cash prices and multiple tracks.
Read more ⬇️
April 22, 2025 at 1:03 PM
FOMO25 accepted at #MICCAI2025! 🚀
Excited to announce the first challenge at MICCAI focusing on the development of self-supervised pretraining of foundation models for brain MRI! 🧠
With access to a large-scale dataset, codebase, cash prices and multiple tracks.
Read more ⬇️
Excited to announce the first challenge at MICCAI focusing on the development of self-supervised pretraining of foundation models for brain MRI! 🧠
With access to a large-scale dataset, codebase, cash prices and multiple tracks.
Read more ⬇️